启发式
计算机科学
启发式
集合(抽象数据类型)
多样性(控制论)
产品(数学)
特征(语言学)
机器学习
管理科学
运筹学
人工智能
经济
数学
操作系统
哲学
语言学
程序设计语言
几何学
标识
DOI:10.1016/j.jbusres.2014.02.015
摘要
Consumers often choose products by first forming a consideration set and then choosing from among considered products. When there are many products to screen (or many features to evaluate), it is rational for consumers to use consider-then-choose decision processes and to do so with heuristic decision rules. Managerial decisions (product development, marketing communications, etc.) depend upon the ability to identify and react to consumers' heuristic consideration-set rules. We provide managerial examples and review the state-of-the-art in the theory and measurement of consumers' heuristic consideration-set rules. Advances in greedoid methods, Bayesian inference, machine-learning, incentive alignment, measurement formats, and unstructured direct elicitation make it feasible and cost-effective to understand, quantify, and simulate “what-if” scenarios for a variety of heuristics. These methods now apply to a broad set of managerial problems including applications in complex product categories with large numbers of product features and feature-levels.
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